A study on Forensic Pathology: Determining Cause of Death Through Heart Images

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Abstract In forensic pathology, identifying the cause of cardiac death rely on gross inspection of specimens and objectively interprethistopathological findings. To fill this void, the proposed work intends to design an Artificial Intelligence system for analyzingheart valve images for different pathological conditions and to aid forensic applications. This system applies deep learningmethods particularly Conventional Neural Networks in distinguishing segments of the histopathology cardiac images andestimating chances of death. This Artificial Intelligence system is integrated with explainable AI and advances that allowsforensic science professionals to comprehend and have faith in the model. Further, to make the tool easily usable in real-lifeforensic scenarios, a web interface is built for easy accessibility by the forensic agents involved and medical professionals inthe course of their work. The overall aim is to minimise the human factors, increase the efficiency of diagnostics, and increasethe speed of the forensic procedures, providing the effective tool for both forensic and clinical uses.
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A study on Forensic Pathology: Determining Cause of Death Through Heart Images | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article A study on Forensic Pathology: Determining Cause of Death Through Heart Images Kariveda Trisha, M Vivek Srikar Reddy, Nichenametla Hima Sree, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6491773/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In forensic pathology, identifying the cause of cardiac death rely on gross inspection of specimens and objectively interprethistopathological findings. To fill this void, the proposed work intends to design an Artificial Intelligence system for analyzingheart valve images for different pathological conditions and to aid forensic applications. This system applies deep learningmethods particularly Conventional Neural Networks in distinguishing segments of the histopathology cardiac images andestimating chances of death. This Artificial Intelligence system is integrated with explainable AI and advances that allowsforensic science professionals to comprehend and have faith in the model. Further, to make the tool easily usable in real-lifeforensic scenarios, a web interface is built for easy accessibility by the forensic agents involved and medical professionals inthe course of their work. The overall aim is to minimise the human factors, increase the efficiency of diagnostics, and increasethe speed of the forensic procedures, providing the effective tool for both forensic and clinical uses. Health sciences/Health care/Medical imaging Health sciences/Cardiology Biological sciences/Computational biology and bioinformatics/Machine learning Forensic Pathology Cause of Death Prediction Cardiac Images Analysis Deep Learning Diffusion Models Explainable AI Diagnostic Accuracy Full Text Additional Declarations No competing interests reported. Supplementary Files Datasetinformation.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6491773","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":461539809,"identity":"2527016c-19ae-4081-8072-30b944ae0371","order_by":0,"name":"Kariveda Trisha","email":"","orcid":"","institution":"Amrita Vishwa Vidyapeetham University","correspondingAuthor":false,"prefix":"","firstName":"Kariveda","middleName":"","lastName":"Trisha","suffix":""},{"id":461539810,"identity":"e9cbae64-10a8-4ba4-8eb2-5fbf12bd38e4","order_by":1,"name":"M Vivek Srikar Reddy","email":"","orcid":"","institution":"Amrita Vishwa Vidyapeetham 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